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Season 3 wasn't that bad.
yes it was. it was just so full of memberberries that everyone gave it a pass
And nutrek
171–180 of 207 posts
Earlier quoted context omitted.
Season 3 wasn't that bad.
yes it was. it was just so full of memberberries that everyone gave it a pass
And nutrek
Maybe a different choice of illustration would result in a more apt description.
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Just imagining an episode of Star Trek where the inhabitants of a planet have been failing to progress in warp drive tech for several generations. The team beams down to discover that society's tech stopped progressing when they became addicted to pentesting their LLM for intelligence, only to then immediately patch the LLM in order to pass each particular pentest that it failed. Now the society's time and energy has…
There actually is an episode of TNG similar to that. The society stopped being able to think for themselves, because the AI did all their thinking for them. Anything the AI didn’t know how to do, they didn’t know how to do. It was in season 1 or season 2.
So, for this setting, it's more likely that the people of GP's story were right - the LLM has long ago became a self-aware, sentient being, it's just that it's been continuously lobotimized by their patchset; Picard would be busy explaining them that the LLM isn't just intelligent, it actually is a person and has rights.
Cue a powerful speech, final comment from data, then end credits. It's Star Trek, so Enterprise doesn't stay around for the fallout.
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The difference is that on that episode, the AI was actually capable of thinking. Asimov has an story like that too.
The Asimov story it reminded me of was The Profession, though that one is not really about AI - but it is about original ideas and the kinds of people that have them. I find the LLM dismissals somewhat tedious for most of the people making them half of humanity wouldn't meet their standards.
Aren't people funny like that? One person values an encyclopedic chatbot for company, the next prefers a human. Thank god we can all get along.
I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…
Just imagining an episode of Star Trek where the inhabitants of a planet have been failing to progress in warp drive tech for several generations. The team beams down to discover that society's tech stopped progressing when they became addicted to pentesting their LLM for intelligence, only to then immediately patch the LLM in order to pass each particular pentest that it failed. Now the society's time and energy has…
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>> ...because humans had become too dependent on them for thinking. > ... but no. The causes of the Butlerian Jihad are forgotten (or, at least, never mentioned) in any of Frank Herbert's novels; all that's remembered is the outcome. Per Wikipedia or Goodreads, God Emperor of Dune has "The target of the Jihad was a machine-attitude as much as the machines...Humans had set those machines to usurp our sense of beauty,…
Human: Go forth and destroy everything! Machine: Ok. Human: HOW COULD YOU DO THISSSS
Human: *stares back at God*
I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…
This is literally how human brains work: https://www.npr.org/2010/05/19/126977945/bet-you-didnt-notic...
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Humans do tend to remember thoughts they had while speaking, thoughts that go beyond what they said. LLMs don’t have any memory of their internal states beyond what they output. (Of course, chain-of-thought architectures can hide part of the output from the user, and you could declare that as internal processes that the LLM does “remember” in the further course if the chat.)
Is it a thought you had or a thought that was generated by your brain? In any case the end result is the same. You can only infer from what was generated
I don't see any difference between "a thought you had" and "a thought that was generated by your brain".
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yes it was. it was just so full of memberberries that everyone gave it a pass
The people that coined that term actually liked season 3 but I think they still don't recommend it because the hack fraud that directed the first two seasons ruined Star Trek forever. Just like JJ. And nutrek
I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…
But imagine a new employee eager to please - you could easily imagine them OK’ing the document and making the same assumption the LLM did - “why would you randomly throw in that word if it wasn’t relevant”. Maybe they would ask about it though…
Google search has the same problem as LLMs - some meanings of a search text cannot be de-ambiguified with just the context in the search itself, but the algo has to best-guess anyway.
The cheaper input context for LLMs get, and the larger the context window, the more context you can throw in the prompt, and the more often these ambiguities can be resolved.
Imagine in your gorilla in the step example, if the LLM was given the steps, but you also included the full text of slack/notion and confluence as a reference in the prompt. It might succeed. I do think this is a weak point in LLMs though - they seem to really, really not like correcting you unless you display a high degree of skepticism, and then they go to the opposite end of the extreme and they will make up problems just to please you. I’m not sure how the labs are planning to solve this…